At least some known commercial organizations, such as, multinational corporations, often link together multiple, fragmented, and geographically dispersed business units and lines-of-business. For example, each organization may have different departments or units that have different roles within the organization. While operating within a common organization, various interactions can take place. For example, one business unit in an organization may provide a referral to another business unit within the organization.
At least some known customer interactions and referrals are not limited to just one organization. Business relationships can involve the interaction between multiple parties from different organizations that may be driven by a single goal. For example, in at least some known real estate matters, a bank teller at one organization may refer a customer to a personal finance manager in the same organization who, in turn, may refer the customer to a real estate agent at another organization. The real estate agent may then refer the customer to a mortgage broker at yet another organization.
Tracking the origins and identifying a quantification of such referrals and transactions can be challenging within one organization and across multiple organizations. For example, within one organization, the fragmented nature of distinct business units and lines of businesses (LOB) may render complex any attempt to accurately identify and capture the various points of customer interaction involving such cross-line-of-business referrals across the organization. Further, devices operating in separate organizations and/or operating within business units in one organization may execute various different types of mutually-incompatible software applications (with corresponding mutually-incompatible data inputs and outputs). As such, the timely aggregation of data captured across different organizations and/or across different business units in one organization, and the dissemination of the aggregated data can be challenging.